Person Following with Dynamic Obstacle Avoidance

Lingxin Kong1; Guolai Jiang2; Yifeng Tang2; Yongsheng Ou2; Sheng Xu2

10.1109/RCAR58764.2023.10249991

2023

979-8-3503-2719-9

2023 IEEE International Conference on Real-time Computing and Robotics (RCAR)

811-816

17-20 July 2023

Datong, China

Person following is essential for many human-robot interaction applications. However, many existing person-following methods do not consider obstacles that have a serious impact on the person-following. In this paper, we focus on the obstacle avoidance problem in the person-following process and propose a dynamic obstacle avoidance path planning method. Our method integrated trajectory prediction into global and local planning to follow a person and avoid obstacles. The proposed method is applied to a practical robot person-following task as an experiment. The experimental results show that the proposed method can achieve the target person following robustly in the case of obstacles.

Human-robot interaction Real-time systems Trajectory Planning Collision avoidance Task analysis Robots

第一

EI

20234214881124

Collision avoidance ; Motion planning

Robotics:731.5 ; Accidents and Accident Prevention:914.1

IEEE

1.Southern University of Science and Technology (SUSTech)
2.Guangdong Provincial Key Laboratory of Robotics and Intelligent System, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

Lingxin Kong,Guolai Jiang,Yifeng Tang,et al. Person Following with Dynamic Obstacle Avoidance[C],2023:811-816.